Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This specific course emphasizes the integration of machine learning and AI with big data administration, utilizing Google Cloud services.
Description for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Managed Big Data Services: Investigate cloud-based services for the collection, storage, and management of large amounts of data, with a focus on scalability and efficiency.
Machine Learning Fundamentals: Offers a comprehensive comprehension of the potential applications of machine learning by introducing its value proposition and terminology.
Data Analysis Framework: Describes the effective organization and analysis of data in the cloud through the use of contemporary tools and methodologies.
Google Cloud AI Tools: Exhibits the practical application and configuration of machine learning and AI tools that are available on Google Cloud for advanced data processing.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by GoogleCloud
Duration: 4�5 hours per week approx 1 week
Schedule: Flexible
Pricing for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Use Cases for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
FAQs for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Reviews for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Relationchips is an AI data agent that automates dashboards and actions, incorporates tools, and queries data in natural language, all without the need for SQL.
Chat2Report facilitates the conversational AI-driven analysis of over a decade of SEC financial reports for US-listed companies.
EquityResearch.ai offers AI-driven stock analysis and business insights, facilitating investment evaluation through impartial, data-centric reports.
NeoBase is an AI-powered assistant that facilitates natural language interaction, optimization, and administration across multiple databases with complete self-hosting capabilities.
Bindle is a platform that is enabled by AI and is capable of organizing files, enabling AI-driven document search, and enabling users to communicate with documents across multiple web applications.
Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.
This course covers Python programming, TensorFlow for linear regression, and app development for stock market prediction.
Explore the world of AI-powered language processing by acquiring the skills necessary to construct chatbots, analyze sentiment, and incorporate AI insights into practical applications.
Develop your skills in image processing, augmented reality, and object recognition to prepare yourself to create cutting-edge AI-powered visual apps.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.
Featured Tools
This program instructs instructors on the ethical and successful integration of AI, while promoting innovation and critical thinking among students.
Explore the world of AI-powered language processing by acquiring the skills necessary to construct chatbots, analyze sentiment, and incorporate AI insights into practical applications.
A structured guide to the study of business opportunities in the chatbot space, as well as the comprehension, design, and deployment of chatbots using Watson Assistant.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.
Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.